Dynamic adjustment method for network data transmission bandwidth

Abstract

The present invention provides a method for dynamically adjusting network data transmission bandwidth, comprising: multiple mobile terminals transmitting data upload request signals to a data storage terminal, the data storage terminal transmitting reception signals to the multiple mobile terminals; the i-th mobile terminal receiving the k-th reception signal transmitted by the data storage terminal at time t; calculating a complex envelope signal of the total amount of signals transmitted by the data storage terminal to the i-th mobile terminal; performing filtering and denoising processing to obtain a restored true signal; dynamically adjusting the bandwidth allocation coefficient of the data storage terminal, and the i-th mobile terminal dynamically uploading data values ​​to the data storage terminal in real time based on the adjusted bandwidth allocation coefficient. The present invention performs data filtering and restoration based on the signals received during simultaneous multipath data transmission between the data transmission terminal and the multiple mobile terminals requiring data upload, and accordingly performs real-time dynamic bandwidth adjustment to maintain a data packet loss rate below a threshold while simultaneously transmitting data to the data storage terminal through multiple paths.

Description

Technical Field

[0001] The present invention belongs to the technical field of network data transmission, and in particular relates to a method for dynamically adjusting network data transmission bandwidth. Background Art

[0002] As communication networks continue to transform and upgrade towards digitalization and intelligence, service diversification and network heterogeneity are deepening and intensifying. Numerous new business applications, such as the Internet of Vehicles and remote control, are emerging. These new services place increasingly stringent demands on service quality assurance. Their critical business data is extremely latency-sensitive, requiring end-to-end latency to be controlled to milliseconds or even microseconds, latency jitter to be controlled to microseconds, and reliability to exceed 99.99%. Industrial services require intelligent digital networks to provide deterministic service assurance, a requirement that traditional network technologies struggle to meet. Emerging services not only require communication networks to guarantee low latency to meet latency-sensitive demands, but also demand high bandwidth. This means that while ensuring low latency, the network must also ensure dynamic bandwidth adjustments during data transmission to ensure the fastest upload speed to data storage.

[0003] In the prior art, Chinese patent application number 202010838169.X discloses a system and method for achieving rapid data transmission between network devices. The system monitors the amount of data to be transmitted by interconnected interactive network devices and the channel capacity of the access channel. The access channel theoretical maximum transmission rate analysis module is used to determine the maximum amount of data transmitted by the current access channel within a limited time, and compares the maximum amount of data with the amount of data to be transmitted between the current devices. The access channel increased channel bandwidth analysis module is used to analyze and regulate using the bandwidth of the access channel. The preferred channel secondary data transmission marking module is used to mark the channels within the increased bandwidth and monitor the parameters of channel transmission between interactive network devices. The interconnected device real-time transmission scheduling module is used to monitor the status of devices connected to each other in real time and respond to successful data transmission in real time. However, it does not perform data filtering and restoration based on the signal reception of simultaneous multipath data transmission between the data transmission end and multiple mobile ends that need to upload data, and further perform real-time dynamic bandwidth adjustment based on this, so that the data packet loss rate is kept below the threshold, and the data is transmitted to the data storage end simultaneously with other mobile ends at the maximum bandwidth. Therefore, there is an urgent need for a method for dynamic adjustment of network data transmission bandwidth. Summary of the Invention

[0004] The present invention addresses these shortcomings by providing a method for dynamically adjusting network data transmission bandwidth. This method filters and restores data based on the signals received during simultaneous multipath transmission between a data transmission terminal and multiple mobile terminals that need to upload data. This method then dynamically adjusts the bandwidth in real time, ensuring that the packet loss rate remains below a threshold while simultaneously transmitting data to the data storage terminal using the maximum bandwidth and multipath transmission with other mobile terminals.

[0005] The present invention provides the following technical solution: a method for dynamically adjusting network data transmission bandwidth, wherein the method dynamically adjusts bandwidth after performing signal processing in a MIMO system based on an adaptive method, thereby ensuring that dynamic traffic requirements are met during network data transmission, and comprises the following steps:

[0006] S1: Multiple mobile terminals send data upload request signals to the data storage terminal, and the data storage terminal sends reception signals to the multiple mobile terminals;

[0007] S2: The i-th mobile terminal receives the k-th receiving signal sent by the data storage terminal at time t;

[0008] S3: Calculate the total complex envelope signal of the signal transmitted by the data storage end to the i-th mobile end;

[0009] S4: performing filtering and denoising on the total complex envelope signal of the signal transmitted from the data storage end to the i-th mobile phone end, calculated in step S3, to obtain a restored real signal;

[0010] S5: The real signal obtained by restoration , dynamically adjust the bandwidth allocation coefficient of the data storage end, and the i-th mobile end dynamically uploads the data value data storage end in real time according to the adjusted bandwidth allocation coefficient.

[0011] Furthermore, the S3 step includes:

[0012] S31: Calculate the kth received signal transmitted by the base station at time t received by the i-th mobile terminal :

[0013] ;

[0014] in, The signal is received by the i-th mobile terminal The delay, for The amplitude of for The phase, is the difference between the frequencies of the signals sent and received by the i-th mobile terminal, T is a sampling period, , , for The reception coefficient, for Phase shift; i=1,2,…,N; k=1,2,…K; K is the total number of data storage terminals participating in network data transmission, and N is the total number of mobile terminals participating in network data transmission; The transmission frequency of the data storage terminal transmitting and receiving signals;

[0015] S32: Calculate the total amount of signals transmitted by the kth data storage terminal to all mobile terminals The calculation formula is:

[0016] ;in, 、 The kth data storage end transmits and receives the zero-degree phase component and the ninety-degree phase component of the signal respectively;

[0017] S33: Definition is the complex baseband envelope signal of the data storage end transmitting and receiving signals, where μ is an imaginary number, and is calculated based on this The complex envelope signal : ;in, is the periodic interference at time t, is Gaussian white noise.

[0018] Furthermore, in the step S32, the kth data storage terminal transmits the zero-degree phase component of the received signal. and the ninety-degree phase component The calculation formulas are as follows:

[0019] ;

[0020] .

[0021] Furthermore, in the step S31 The reception coefficient The calculation formula is as follows:

[0022] ;in, is the frequency difference between the transmitted and received signals at the kth data storage terminal, It is the phase shift of the received signal transmitted by the data storage end.

[0023] Furthermore, the S4 step includes the following steps:

[0024] S41: Calculate the periodic interference at time t in step S33 : ;middle, is the amplitude of the harmonics in the signal when the kth data storage terminal transmits and receives the signal at time t, Calculate the weight for the periodic interference when the kth data storage terminal transmits and receives the signal, where Re{} is the real part function of the independent variable; is the angular frequency of the signal transmitted and received by the data storage end, ;

[0025] S42: Build Minimize the solution model: ; Where, Ω is the error minimization mean;

[0026] S43: continuously iteratively updating the solution result of step S42;

[0027] S44: Calculate the weight of the qth generation optimal periodic interference obtained , brought into the step S33 to calculate the complex envelope signal In the formula, the signal-to-noise ratio at this time is calculated to determine whether it is less than the signal-to-noise ratio threshold. If so, the iteration is stopped; otherwise, the iteration of step S43 is repeated continuously.

[0028] Furthermore, in the step S44, the weight is calculated based on the qth generation optimal periodic interference obtained by solving The formula for calculating the signal-to-noise ratio is as follows:

[0029] ;in, is the signal-to-noise ratio of the qth generation result, Indicates that when periodic interference is calculated weight is the optimal periodic interference weight obtained by the qth generation iterative optimization The complex envelope signal at ;

[0030] Signal-to-noise ratio threshold The calculation formula is as follows: ;in, is the power spectrum density of the periodic interference signal, is the bandwidth of the periodic interference.

[0031] Furthermore, the S5 step includes:

[0032] S51: Calculate the bandwidth allocation coefficient for the i-th mobile terminal to transmit data to the data storage terminal after receiving the k-th receiving signal sent by the data storage terminal. : ,in, The total bandwidth of the data storage end receiving uploaded data;

[0033] S52: During data transmission based on the TCP protocol, the bandwidth allocation coefficient is continuously increased under the bandwidth allocation limitation conditions: ; Among them, the bandwidth allocation restriction conditions are: ,σ is the bandwidth allocation increase coefficient, is the bandwidth allocation coefficient for the i-th mobile terminal to transmit data to the data storage terminal after receiving the k+1-th reception signal sent by the data storage terminal;

[0034] S53: After increasing the bandwidth allocation coefficient, calculate the data packet loss rate when the i-th mobile terminal receives the k+1-th receiving signal sent by the data storage terminal and uploads data to the data storage terminal :

[0035] ;

[0036] S54: Judgment Is the packet loss rate less than or equal to the data packet loss rate threshold? If yes, then repeat the steps S51-S52 to upload the data of the i-th mobile terminal to the data storage terminal. Otherwise, the bandwidth allocation coefficient for the i-th mobile terminal uploading data to the data storage terminal upon receiving the k+1-th receiving signal sent by the data storage terminal is Make a reduction, and use the bandwidth allocation coefficient after the reduction Continue uploading data;

[0037] ;in, Bandwidth allocation coefficient The reduction weight coefficient is: .

[0038] Furthermore, the bandwidth allocation increase coefficient σ is calculated using the following calculation method:

[0039] ;in, The time it takes for the i-th mobile terminal to upload data to the data storage terminal and obtain its confirmation after receiving the k-th reception signal sent by the data storage terminal. ; max is the maximum value function.

[0040] The beneficial effects of the present invention are:

[0041] 1. The method provided by the present invention decomposes the received signal sent by the data storage end into a zero-degree phase component and a ninety-degree phase component, and then calculates the complex envelope signal. The components can respectively describe the amplitude and phase of the signal, so that the receiving end can accurately restore the original signal, avoiding the defect that certain key information of the signal may be lost, and at the same time reducing the phenomenon of envelope signal restoration distortion caused by noise, fading, and interference that the transmission signal may be subject to during network data transmission in the wireless channel. The use of zero-degree and ninety-degree phase components and complex envelope signals helps to improve the accuracy of signal restoration. When using the complex envelope signal for restoration, the mobile terminal can detect and compensate for phase changes caused by channel fading to ensure signal quality.

[0042] 2. In the process of filtering and denoising the periodic interference in the envelope signal, the present invention iteratively updates the calculation weights of the periodic interference, and constructs The calculation model calculates the weights based on the mutual correlation matrix C, self-compensating matrix P and double conjugate matrix D between errors and samples, and can adaptively adjust the weights according to real-time data. This adaptive capability is very important for communication systems such as MIMO systems or beamforming where channel conditions change rapidly. The optimal periodic interference calculation weights obtained by dynamic and real-time adjustment in an adaptive manner can cope with environmental changes and improve system flexibility. In adaptive filtering and MIMO systems, it can quickly track channel changes and reduce errors. It also supports the processing of multi-dimensional signals. The self-compensating matrix and the double conjugate matrix are suitable for processing multi-dimensional signals in complex form, such as multi-input and multi-output signals in MIMO systems. The mutual correlation matrix can capture the correlation between signal samples and is used for optimization processing between multiple signal sources (such as beamforming and array signal processing). Therefore, the optimal periodic interference calculation weights obtained by the method provided by the present invention are finally dynamically adjusted. It supports multi-dimensional signal optimization and is suitable for data transmission in complex network communication systems such as MIMO communication systems, and can achieve optimal network signal transmission restoration.

[0043] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0044] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be described in more detail below based on embodiments and with reference to the accompanying drawings, wherein:

[0046] Figure 1 A schematic diagram of data transmission between a data storage terminal and multiple mobile terminals in a method for dynamically adjusting network data transmission bandwidth according to the present invention;

[0047] Figure 2 The complex envelope signal of the total amount of the transmitted signal obtained by reverse reconstruction in step S3 in the method provided by the present invention , zero-degree phase component and the ninety-degree phase component Schematic diagram of the change of amplitude with emission distance;

[0048] Figure 3 A schematic diagram showing a comparison of a fluctuation curve and a signal-to-noise ratio threshold during the iterative optimization of the complex envelope signal in step S4 of the method provided by the present invention;

[0049] Figure 4 This is a comparison chart of the dynamic bandwidth adjustment effects of the method provided by the present invention and comparative examples 1-3. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] The present invention provides a method for dynamically adjusting the bandwidth of network data transmission. The method dynamically adjusts the bandwidth after processing the signal in the MIMO system based on an adaptive method, so as to ensure that the dynamic flow demand is met during the network data transmission process. Figure 1 As shown, the method provided by the present invention performs network dynamic adjustment on the data transmission end and the data transmission between multiple mobile ends. Figure 1 In the example, User1 is the first mobile terminal of the MIMO system, User2 is the second mobile terminal, Useri is the i-th mobile terminal, and UserN is the N-th mobile terminal. All of them perform data network transmission with the data storage terminal. The data network method provided by the present invention includes the following steps:

[0052] S1: Multiple mobile terminals send data upload request signals to the data storage terminal, and the data storage terminal sends receiving signals to multiple mobile terminals;

[0053] S2: The i-th mobile terminal receives the k-th receiving signal sent by the data storage terminal at time t;

[0054] S3: Calculate the total complex envelope signal of the signal transmitted from the data storage terminal to the i-th mobile terminal;

[0055] S4: Filter and denoise the total complex envelope signal of the signal transmitted from the data storage end to the i-th mobile terminal, calculated in step S3, to obtain a restored real signal;

[0056] S5: The real signal obtained by restoration , the bandwidth allocation coefficient of the data storage end is dynamically adjusted, and the i-th mobile end dynamically uploads data values ​​to the data storage end in real time based on the adjusted bandwidth allocation coefficient.

[0057] The S3 steps include:

[0058] S31: Calculate the kth received signal transmitted by the base station at time t received by the i-th mobile terminal :

[0059] ;

[0060] in, The signal is received by the i-th mobile terminal The delay, for The amplitude, for The phase, is the difference between the frequencies of the signals sent and received by the i-th mobile terminal, T is a sampling period, , , for The reception coefficient, for Phase shift; i=1,2,…,N; k=1,2,…K; K is the total number of data storage terminals participating in network data transmission, and N is the total number of mobile terminals participating in network data transmission; The transmission frequency of the data storage terminal transmitting and receiving signals;

[0061] In data transmission and wireless communications, a data storage device sends signals to multiple mobile devices, which then need to process the received signals to accurately restore the original signal. Decomposing the signal using its zero- and ninety-degree phase components, and further restoring the transmitted signal's complex envelope, is both crucial and necessary.

[0062] S32: Calculate the total amount of signals transmitted by the kth data storage terminal to all mobile terminals The calculation formula is:

[0063] ;in, 、 The kth data storage end transmits and receives the zero-degree phase component and the ninety-degree phase component of the signal respectively;

[0064] S33: Definition is the complex baseband envelope signal of the data storage end transmitting and receiving signals, where μ is an imaginary number, and is calculated based on this The complex envelope signal :

[0065] ;in, is the periodic interference at time t, is Gaussian white noise. Figure 2 As shown in FIG. 1 , the total amount of signals transmitted by the kth data storage terminal to all mobile terminals is calculated using steps S31-S33 of the method provided by the present invention. The complex envelope signal , and the zero-degree phase component of the received signal sent by the k-th data storage terminal in step S32 and the ninety-degree phase component The amplitude changes with the launch distance (horizontal axis) in the same coordinate system. Figure 2 As shown, the zero-degree phase component Represents the part of the signal that is in phase with the carrier, the ninety-degree phase component Represents the part of the signal that is 90 degrees out of phase with the carrier. is the complex envelope signal of the K data storage terminals transmitting and receiving signals, so, It is also equal to the total amount of the received signal transmitted by the kth data storage terminal calculated based on the zero-degree and ninety-degree phase components of step S32, that is, Therefore, if Figure 2 As shown, after step S32, the total signal is decomposed, and the complex envelope of the zero-degree phase component and the ninety-degree phase component is again performed in step S33. The decomposition of the two components ensures that the phase and amplitude information of the signal are completely preserved, avoiding information loss due to carrier aliasing. In addition, the decomposition of the two components maps the signal to the complex plane, making it possible to use a complex number representation of the signal model for more efficient processing.

[0066] In step S32, the kth data storage terminal transmits the zero-degree phase component of the received signal and the ninety-degree phase component The calculation formulas are as follows:

[0067] ;

[0068] .

[0069] In step S31 The reception coefficient The calculation formula is as follows:

[0070] ;in, is the frequency difference between the transmitted and received signals at the kth data storage terminal, It is the phase shift of the received signal transmitted by the data storage end.

[0071] In order to filter and reduce noise on the complex envelope signal and improve the accuracy of signal restoration in multipath propagation during mobile communication, as another preferred embodiment of the present invention, step S4 includes the following steps:

[0072] S41: Calculate the periodic interference at time t in step S33 :

[0073] ;in, is the amplitude of the harmonics in the signal when the kth data storage terminal transmits and receives the signal at time t, Calculate the weight of the periodic interference when the k-th data storage terminal transmits and receives the signal, Re{} is the real part function of the independent variable, that is, To take the independent variable The real part of the result; is the angular frequency of the data storage end transmitting and receiving signals, ;

[0074] S42: Build Minimize the solution model:

[0075] ;

[0076] S43: continuously iteratively update the solution of step S42;

[0077] S44: Calculate the weight of the qth generation optimal periodic interference obtained , bring it into step S33 to calculate the complex envelope signal In the formula, the signal-to-noise ratio at this time is calculated to determine whether it is less than the signal-to-noise ratio threshold. If so, the iteration is stopped; otherwise, the iteration of step S43 is repeated continuously.

[0078] In step S44, the weight is calculated based on the qth generation optimal periodic interference obtained by the solution The formula for calculating the signal-to-noise ratio is as follows:

[0079] ;in, Indicates that when periodic interference is calculated weight is the optimal periodic interference weight obtained by the qth generation iterative optimization The complex envelope signal at ,exist Figure 3 The middle is represented by the light blue curve; Figure 3The light yellow curve in the figure represents the weight coefficient of the proportion of S(t) that has not undergone the periodic interference n(t) of step S44. The signal situation under the optimization iteration is that after only 50 generations of iteration, the signal-to-noise ratio is always greater than the signal-to-noise ratio threshold (about 13dB);

[0080] The calculation formula of the signal-to-noise ratio threshold is as follows:

[0081] ;in, is the power spectrum density of the periodic interference signal, is the bandwidth of the periodic interference.

[0082] To improve To minimize the accuracy of the complex envelope signal obtained by solving the problem, the present invention further optimizes the calculation result in step S43. Preferably, in step S43, the qth generation optimal periodic interference calculation weight obtained by solving the model constructed in step S42 is continuously iteratively optimized, including the following steps:

[0083] S431: Calculate the qth generation complex envelope signal obtained in the iterative process Estimated value of :

[0084] ;in, , ; H is the total number of iterations, is the hth generation complex envelope signal obtained in the iterative process The true value of is the qth generation complex envelope signal obtained in the iterative process The true value of the true value of ;

[0085] S432: Calculate the qth generation complex envelope signal Estimated value of The deviation from the mean of the total samples of the H generation iterations :

[0086] ;in, Calculate the weight for the hth generation periodic interference; is the total sample mean of H generations of iterations ;

[0087] S433: Build Deviation The complex conjugate of The cross-correlation vector :

[0088] ;

[0089] And construct the cross-correlation vector matrix C: ; The element cross-correlation vector in the cross-correlation vector matrix C Provides sample estimates and the complex conjugate of the error The correlation between them makes it possible to more accurately describe the relationship between the signal and the noise when calculating the weight. In the process of minimizing the error, the influence of the noise on the iterative result can be effectively eliminated, making the final calculated weight more accurate.

[0090] S434: Calculate self-compensation vector : ;

[0091] And construct the self-compensating matrix P: ;

[0092] S435: Calculating Biconjugate Vectors : ;

[0093] And construct the biconjugate matrix D: ;

[0094] S436: The S42 step constructed The minimization solution model is converted into matrix form:

[0095] ;

[0096] S437: Obtain the optimal periodic interference calculation weight according to the matrix form converted in step S436 :

[0097] .

[0098] Self-complementing vectors in the self-complementing matrix P Including the qth generation complex envelope signal Estimated value of The deviation and its complex conjugate The product of the biconjugate matrix D is the biconjugate vector Including conjugate complex numbers The use of the self-compensating matrix P and the double conjugate matrix D takes into account the phase information of the signal, which is particularly effective for processing complex signals such as wireless communication signals. The cross-correlation vector matrix C can capture the relationship between different signals and improve the stability of the system in complex environments such as multipath propagation and interference. Finally, the optimal periodic interference weight is obtained by re-conjugating the matrices, doing the difference and product between the inverse matrices. It can ensure phase adaptation under channel distortion, thereby ensuring the calculation weight of periodic interference. Robustness and stability, suitable for complex environments such as multipath and non-ideal channels. Figure 3 As shown in the figure, in mobile communications, the decomposition and complex envelope processing of the zero-degree phase component and the ninety-degree phase component can effectively compensate for the superposition distortion of the received signal caused by multipath propagation. The decomposition of the zero-degree phase component and the ninety-degree phase component enables the mobile terminal to demodulate the signal more efficiently, reduce the bit error rate (BER), and ensure the stability of communication. At the same time, through multiple iterative optimizations, the true state of the signal is restored, the harmonic noise in the signal is reduced, and the signal-to-noise ratio (SNR) is lower than the signal-to-noise ratio threshold, thereby improving the accuracy of demodulation.

[0099] Dynamic bandwidth allocation is a key mechanism for flow control in the TCP protocol for network data transmission. The bandwidth allocation coefficient determines the maximum amount of data that the sender can send before receiving an acknowledgment, thereby avoiding network congestion. It also determines the transmission speed of data when it is uploaded to the data storage end. Therefore, as another preferred embodiment of the present invention, step S5 includes:

[0100] S51: Calculate the bandwidth allocation coefficient for transmitting data from the i-th mobile terminal to the data storage terminal after receiving the k-th receiving signal from the data storage terminal. : ,in, The total bandwidth of the data storage end receiving uploaded data;

[0101] S52: During data transmission based on the TCP protocol, under the constraints of bandwidth allocation limitations, the bandwidth allocation coefficient is continuously increased to improve bandwidth utilization and quickly transmit real signals:

[0102] ; Among them, the bandwidth allocation restriction conditions are: ,σ is the bandwidth allocation increase coefficient, is the bandwidth allocation coefficient for data transmission from the i-th mobile terminal to the data storage terminal after receiving the k+1-th receiving signal from the data storage terminal;

[0103] The bandwidth allocation increase coefficient σ is calculated as follows:

[0104] ;in, The time it takes for the i-th mobile terminal to upload data to the data storage terminal and obtain its confirmation after receiving the k-th receiving signal from the data storage terminal. ; max is the maximum value function;

[0105] S53: After increasing the bandwidth allocation coefficient, calculate the data packet loss rate when the i-th mobile terminal receives the k+1-th receiving signal sent by the data storage terminal and uploads data to the data storage terminal :

[0106] ;

[0107] S54: Judgment Is the packet loss rate less than or equal to the data packet loss rate threshold? If yes, then repeat steps S51-S52 to upload the data of the i-th mobile terminal to the data storage terminal. Otherwise, the bandwidth allocation coefficient of the i-th mobile terminal when it receives the k+1-th receiving signal sent by the data storage terminal to upload data to the data storage terminal is The bandwidth allocation coefficient after reduction is Continue uploading data;

[0108] ;in, Bandwidth allocation coefficient The reduction weight coefficient; .

[0109] Comparative Example 1

[0110] This comparative example is substantially the same as the method provided by the present invention, except that, in step S3, when calculating the complex envelope signal of the total signal transmitted from the data storage end to the i-th mobile end, decomposition of the zero-degree phase component and the ninety-degree phase component is not performed, and an inverse Fourier transform is directly performed to solve the complex envelope signal.

[0111] Comparative Example 2

[0112] This comparative example is substantially the same as the method provided by the present invention, except that after calculating the total complex envelope signal transmitted by the data storage end to the i-th mobile end in step S3, in the filtering and denoising process of step S4, the signal-to-noise ratio threshold of the filtered signal is not limited and solved, nor is the cross-correlation vector matrix C, the self-compensation matrix P and the biconjugate matrix D constructed, and the optimal periodic interference calculation weight is performed. The solution is directly based on the least squares method.

[0113] Comparative Example 3

[0114] During the process of dynamic bandwidth adjustment, no data packet loss rate is calculated. Less than or equal to the packet loss rate threshold The limit is not the packet loss rate Greater than the packet loss rate threshold In order to reduce the weight coefficient The weight of the k+1th signal is used to reduce the bandwidth allocation coefficient of the transmission. It only determines whether each signal transmission exceeds the bandwidth limit of the data storage end when it is synchronized with the signals of other mobile ends and transmitted to the data storage end, and decides whether to transmit the signal of the mobile end or reduce the data throughput of the signal transmission.

[0115] like Figure 4 As shown, it is a bar chart comparing the throughput of a mobile terminal when the data storage terminal and multiple mobile terminals perform multipath transmission according to the method of the present invention and the methods of Comparative Examples 1 to 3. The horizontal axis is the number of mobile terminals. The blue column is the method provided by the present invention, the yellow column is the method of Comparative Example 1, the green column is the method of Comparative Example 2, and the red column is the method of Comparative Example 3. Figure 4 As shown, the method provided by the present invention performs data filtering and restoration based on the signal reception of simultaneous multipath data transmission between a data transmission end and multiple mobile ends that need to upload data, and further performs real-time dynamic bandwidth adjustment based on this, so that the data loss rate is kept below a threshold, and data is transmitted to the data storage end simultaneously with other mobile ends using the maximum bandwidth. This allows the original receiving signal emitted by the data storage end to be accurately restored at the multiple mobile ends, and effectively improves the throughput of the data storage end during the multipath transmission between the multiple mobile ends and the data storage end, so that the data of the multiple mobile ends can be uploaded and stored using the maximum allowable receiving bandwidth.

[0116] The dynamic method for network data transmission bandwidth provided in the present application can be in the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Machine-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of machine-readable storage media include but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0117] It should be noted that the serial numbers of the above-mentioned embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. In this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. And the terms "include", "comprise" or any other variations thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method that includes a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements that are inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a..." does not exclude the presence of other identical elements in the process, device, article or method that includes the element.

[0118] The above are merely specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not limited to these embodiments, but is to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for dynamically adjusting network data transmission bandwidth, wherein the method dynamically adjusts bandwidth after performing signal processing in a MIMO system based on an adaptive method, thereby ensuring that dynamic traffic requirements are met during network data transmission, and wherein: The following steps are involved: S1: Multiple mobile terminals send data upload request signals to the data storage terminal, and the data storage terminal sends reception signals to the multiple mobile terminals; S2: The i-th mobile terminal receives the k-th receiving signal sent by the data storage terminal at time t; S3: Calculate the total complex envelope signal of the signal transmitted by the data storage end to the i-th mobile end; S4: performing filtering and denoising on the total complex envelope signal of the signal transmitted from the data storage end to the i-th mobile phone end, calculated in step S3, to obtain a restored real signal; S5: The real signal obtained by restoration , dynamically adjusting the bandwidth allocation coefficient of the data storage end, and the i-th mobile end dynamically uploading the data value to the data storage end in real time according to the adjusted bandwidth allocation coefficient; The S3 step includes: S31: Calculate the kth received signal transmitted by the base station at time t received by the i-th mobile terminal : ； in, The signal is received by the i-th mobile terminal The delay, for The amplitude, for The phase, is the difference between the frequencies of the signals sent and received by the i-th mobile terminal, T is a sampling period, , , for The reception coefficient, for Phase shift; i=1,2,…,N; k=1,2,…K; K is the total number of data storage terminals participating in network data transmission, and N is the total number of mobile terminals participating in network data transmission; The transmission frequency of the data storage terminal transmitting and receiving signals; S32: Calculate the total amount of signals transmitted by the kth data storage terminal to all mobile terminals The calculation formula is: ;in, 、 The kth data storage end transmits and receives the zero-degree phase component and the ninety-degree phase component of the signal respectively; S33: Definition is the complex baseband envelope signal of the data storage end transmitting and receiving signals, where μ is an imaginary number, and is calculated based on this The complex envelope signal : ;in, is the periodic interference at time t, is Gaussian white noise; The S4 step includes the following steps: S41: Calculate the periodic interference at time t in step S33 : ;in, is the amplitude of the harmonics in the signal when the kth data storage terminal transmits and receives the signal at time t, Calculate the weight for the periodic interference when the kth data storage terminal transmits and receives the signal, where Re{} is the real part function of the independent variable; is the angular frequency of the data storage end transmitting and receiving signals, ; S42: Build Minimize the solution model: ; Where, Ω is the error minimization mean; S43: continuously iteratively updating the solution result of step S42; S44: Calculate the weight of the qth generation optimal periodic interference obtained , brought into the step S33 to calculate the complex envelope signal In the formula, the signal-to-noise ratio at this time is calculated to determine whether it is less than the signal-to-noise ratio threshold. If so, the iteration is stopped; otherwise, the iteration of step S43 is repeated continuously; In the step S44, the weight is calculated based on the qth generation optimal periodic interference obtained by solving The formula for calculating the signal-to-noise ratio is as follows: ;in, is the signal-to-noise ratio of the qth generation result, Indicates that when periodic interference is calculated weight is the optimal periodic interference weight obtained by the qth generation iterative optimization The complex envelope signal at ; Signal-to-noise ratio threshold The calculation formula is as follows: ;in, is the power spectrum density of the periodic interference signal, is the bandwidth of the periodic interference; In step S43, the qth generation optimal periodic interference calculation weight obtained by continuously iteratively optimizing the model constructed in step S42 includes the following steps: S431: Calculate the qth generation complex envelope signal obtained in the iterative process Estimated value of : ;in, , ; H is the total number of iterations, is the hth generation complex envelope signal obtained in the iterative process The true value of is the qth generation complex envelope signal obtained in the iterative process The true value of S432: Calculate the qth generation complex envelope signal Estimated value of The deviation from the mean of the total samples of the H generation iterations : ;in, Calculate the weight for the hth generation periodic interference; is the total sample mean of H generations of iterations ; S433: Build Deviation The complex conjugate of The cross-correlation vector : ; and construct the cross-correlation vector matrix C: ; The element cross-correlation vector in the cross-correlation vector matrix C Provides sample estimates and the complex conjugate of the error the correlation between them; S434: Calculate self-compensation vector : ; and construct the self-compensating matrix P: ; S435: Calculating Biconjugate Vectors : ; and construct the biconjugate matrix D: ; S436: The S42 step constructed The minimization solution model is converted into matrix form: ； S437: Obtain the optimal periodic interference calculation weight according to the matrix form converted in step S436 : ; The S5 step includes: S51: Calculate the bandwidth allocation coefficient for the i-th mobile terminal to transmit data to the data storage terminal after receiving the k-th receiving signal sent by the data storage terminal. : ,in, The total bandwidth of the data storage end receiving uploaded data; S52: During data transmission based on the TCP protocol, the bandwidth allocation coefficient is continuously increased under the bandwidth allocation limitation conditions: ; Among them, the bandwidth allocation restriction conditions are: ,σ is the bandwidth allocation increase coefficient, is the bandwidth allocation coefficient for the i-th mobile terminal to transmit data to the data storage terminal after receiving the k+1-th reception signal sent by the data storage terminal; The bandwidth allocation increase coefficient σ is calculated using the following calculation method: ;in, The time it takes for the i-th mobile terminal to upload data to the data storage terminal and obtain its confirmation after receiving the k-th reception signal sent by the data storage terminal. ; max is the maximum value function; S53: After increasing the bandwidth allocation coefficient, calculate the data packet loss rate when the i-th mobile terminal receives the k+1-th receiving signal sent by the data storage terminal and uploads data to the data storage terminal : ; S54: Judgment Is the packet loss rate less than or equal to the data packet loss rate threshold? If yes, then repeat the steps S51-S52 to upload the data of the i-th mobile terminal to the data storage terminal. Otherwise, the bandwidth allocation coefficient for the i-th mobile terminal uploading data to the data storage terminal upon receiving the k+1-th receiving signal sent by the data storage terminal is Make a reduction, and use the bandwidth allocation coefficient after the reduction Continue uploading data; ;in, Bandwidth allocation coefficient The reduction weight coefficient is: .

2. The method for dynamically adjusting network data transmission bandwidth according to claim 1, wherein: In the step S32, the kth data storage terminal transmits the zero-degree phase component of the received signal and the ninety-degree phase component The calculation formulas are as follows: ； 。 3. The method for dynamically adjusting network data transmission bandwidth according to claim 1, wherein: In the step S31 The reception coefficient The calculation formula is as follows: ;in, is the frequency difference between the transmitted and received signals at the kth data storage terminal, It is the phase shift of the received signal transmitted by the data storage end.

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